How Skills Tracking Improves Work Allocation and Workforce Utilization

Learn how skills tracking enhances work allocation and workforce utilization to improve productivity in manufacturing.

Employee skills tracking is an excellent way to stay ahead of the curve in today’s ever-changing manufacturing landscape. Leaders can use this talent management strategy to close worker competency gaps, increase effective training, and hire qualified prospects.

Putting an emphasis on employee skills can also help manufacturers prioritize work allocation and workforce utilization. But what exactly do these two terms mean and how do they relate to tracking skills in manufacturing?

Work allocation is the process of assigning resources and roles to meet the objectives of a given task or production facility. Workforce utilization, meanwhile, refers to how a company or organization effectively utilizes its workforce to meet its operational goals and objectives.

skills tracking and workforce utilization in manufacturing

To keep up with competition, manufacturers should not only try to recruit the best possible hires, but also allocate work in an effective way to retain staff, satisfy customers, and boost profits.

Ultimately, keeping track of skills is a beneficial way to organize a company’s resources to attain sustainable business goals. Implementing a connected worker solution and digitizing skills management processes through smart manufacturing technologies is an effective way for organizations to instantly visualize the skills gaps in teams as well as track workforce skills and quickly assess both team and individual readiness.

Learn more about digital skills tracking and how it improves work allocation and workforce utilization below:

Skills tracking defined

Skills tracking helps ensure that all workers have the necessary expertise to complete tasks to their fullest potential. Basically, it closes the gap between the competencies employees already have and ones they need to further develop.

Every manufacturing firm has a unique set of job requirements and expectations. Tracking worker skills on a regular basis helps a company identify training needs and build workers’ knowledge so that they can meet expected targets. Skills management and tracking software help manufacturers identify and track employee expertise. You can map skills from a centralized library to individual workers, analyze the performance of your teams, and fill any skill gaps that exist.

skills tracking software

In a nutshell, measuring employee proficiencies can boost retention, decrease the amount of time spent on tasks, and improve overall productivity.

Benefits of tracking skills to improve work allocation

Through digitization and effective skills tracking, manufacturing firms can best allocate work to team members based on expertise, credentials, and actual ability. For example, an operator who has more than 10 years of experience using computer-controlled equipment may be a better fit to handle complex machinery than an entry-level worker who lacks that training.

Additionally, with a centralized digital repository managers have a better idea of each employee’s current skills level and potential areas of improvement. Then they can close any skill gaps through training opportunities. In return, workers who receive the necessary training are more likely to thrive in their roles and be productive.

In summary, measuring worker skills can help improve work allocation by:

  • Hiring or assigning current employees to the correct jobs and tasks
  • Facilitating worker development through mentorship and training
  • Retaining high-quality employees

How tracking skills boosts workforce utilization

Workforce utilization refers to how much of an employee’s time is devoted to billable work. Tracking skills can improve this, in turn boosting productivity and profits.

When you measure how efficiently employees are doing their jobs and how well a business manages its resources, you can assure that tasks are done well and see continuous increase in revenue. Think about how many hours of each staff member’s workweek need to be billable to remain profitable and whether they are on track. With a digitized tracking system, manufacturers are able to automate and streamline this process reducing errors, improving productivity, and ensuring success.

Pro Tip

Through the use of smart, connected worker solutions and AI-based workforce insights organizations can deliver continuous, on-the-job learning based on skill tracking and real job performance, promoting reskilling and upskilling efforts enterprise wide.

To summarize, tracking skills can help enhance workforce utilization by:

  • Setting profitable rates for services based on worker output and time billed
  • Compensating employees fairly
  • Gauging whether staff is being overworked or underutilized

By digitizing these tracking processes and implementing AI-driven support, organizations can also visualize, track and offset employee burnout. By taking highly granular connected worker data and using AI to filter out the unnecessary portions, industrial operations are able to not only improve tasks and productivity but better support and empower frontline workers.

Ways to track workforce skills

Tracking employee skills is a great way to improve worker performance and productivity by matching the right person with the right assignment.

One way to track an employee’s skills is through a skills matrix, which is a grid that maps staff credentials and qualifications. A skills matrix helps managers strategize and oversee current and wanted skills for a team, position, department, and more. A skills matrix is usually managed using a spreadsheet, but there are alternatives to skill matrices. For example, cloud-based skills management software can help identify and track employee competence and correlate it with actual job performance. The software can also help managers filter employee databases by skills to assemble teams or assign work based on specific qualifications.

skills matrix

Leadership can also track competencies through a skills taxonomy. Taxonomies help classify and organize skills into groups to better understand which skills employees have and which they should learn. Essentially, these structured lists help management identify and track skills to better allocate resources and worker training opportunities.

Lastly, a skills-tracking application can include AI-based software to identify and measure worker expertise and actual job performance. This is an excellent method for intelligently assigning work through skills mapping, optimizing training programs, and more. With AI-based insights and connected worker technology, organizations can bridge the gap between the training room and the shop floor, integrating training into the flow of work and creating an environment of continuous learning.

Skills management with Augmentir

Augmentir offers top-notch solutions to easily track and manage your frontline’s skillset. Our connected worker solution provides customized dashboards to streamline processes to improve workforce management, skills management, and deliver in-line training and support at the point of work, closing skills gaps at the moment of need.

If you are interested in learning how Augmentir can help improve your skills management, skills tracking, and workforce development – request a live demo.

 

See Augmentir in Action
Get in Touch for a Personalized Demo

 

Book A Demo

Why Quality is Important in Manufacturing

Learn why implementing quality in manufacturing is crucial for product creation, risk management, and more.

Quality in manufacturing depends on effective quality control (QC), a set of procedures used to measure and test products for compliance. The main function of QC is to ensure that all goods are free of defects, meet client expectations, and adhere to industry best practices.

Products have the potential either to increase customer satisfaction or to create legal and financial complications if deficiencies are found. In the current era where consumers are increasingly conscious of product safety and quality, it is paramount that manufacturers are doing all they can to ensure products meet all quality standards. Quality goods can affect a business’s success and advance its credibility to the public. They can also lead to fewer production costs and increases in profit.

With emerging digital technologies such as AI and connected worker solutions, manufacturers can improve quality control, decrease defects, and more. AI-powered connected worker platforms allow manufacturers to standardize quality control, resulting in fewer errors, reduced defects, and streamlined quality processes that are faster and more accurate.

Explore the following content to get a better idea of why quality is crucial and ways to improve it:

quality in manufacturing

Defining quality on industrial frontlines

Quality in the manufacturing realm is all about following procedures to meet product and compliance specifications. Once the standard for quality is set, the rest is about meeting product expectations through standardized procedures.

Quality in production can be broken down into three factors: design, quality control, and quality management.

Design: A product can be significantly improved by design. For example, goods should be made with the right materials to ensure functionality and a longer shelf life.

Quality control: The level of quality is improved when waste and product defects are reduced during the QC process.

Quality management: Completing production processes that follow regulatory standards is at the core of quality management.

Pro Tip

By digitizing quality control and quality assurance procedures, manufacturers can ensure a standardized approach towards inspections and quality data collection and improve overall compliance with quality standards.

Quality affects every facet of manufacturing

Production quality is more than just distributing products that people will trust and buy. Though that may be a key factor, quality affects every aspect of manufacturing, from workplace risk management to machine upkeep and inspection.

Quality affects many aspects of production. Examples include the following:

  • Risk management ensures products are safe to use by customers and follow safety protocols. Smart, connected worker solutions are able to improve risk management through standardization and optimization of quality checks.
  • Regulatory compliance is a key component of quality and can help prevent delays in production and fines. With digitized processes in place, manufacturers are able to ensure workers have access to the correct procedures and that tasks are performed in a standardized manner to avoid errors and promote improved compliance.
  • Waste reduction is possible when material resources are conserved and used accordingly in production processes. AI-powered analytics in conjunction with smart, connected worker solutions allow for improved, streamlined processes that are able to reduce waste and improve yield through optimized production.
  • Errors and defects are reduced when procedures are standardized using efficient QC processes to troubleshoot problems. With connected worker solutions and digitized quality control processes, mistakes can be identified as they happen, protecting the production process.
  • Machine upkeep and inspection can be strengthened when industry best practices are implemented. Digitizing machine inspection standards and upkeep notifications and connecting frontline workers via smart, connected worker platforms gives operators the ability to practice preventative and autonomous maintenance and improves overall equipment effectiveness (OEE) and reduces unplanned downtime.

How to Improve Quality in Manufacturing

Quality improvement in manufacturing is vital to ensure a business is performing at its best. Here are some ways to boost quality with real-world examples:

Step 1: Practice lean manufacturing.

Lean manufacturing is the practice of reducing waste in production processes. Waste is defined as anything that does not bring value to the customer. This method requires an examination of your current practices to see which work and which leads to greater waste. The rise of digital technology is making it easier and more practical for manufacturers to connect and digitize their operations and drive further improvements and enhance lean manufacturing strategies.

Real-world application: An injection molding machine was found clogged with mold and was producing products with damaged seams. After resolving this issue by cleaning the machine, the company had less wasted plastic and fewer product malfunctions. With digitized notifications, real-time collaboration, and smart, connected worker solutions, situations like the above can be solved quickly and with reduced impact on production.

standardize and digitize quality assurance procedures

Step 2: Implement total productive maintenance.

Total Productive Maintenance (TPM) focuses on the idea that every employee should do their part to maximize equipment effectiveness. The objective is to create a culture where every worker adjusts and maintains machinery over the course of each shift. Through a combination of digital work instructions and real-time collaboration tools, manufacturers can better implement and improve TPM initiatives. This allows operators to independently complete maintenance tasks at peak performance and improve overall equipment effectiveness (OEE).

Real-world application: Both operators and maintenance staff can perform routine maintenance to check for errors or deficiencies. By implementing connected worker solutions organizations can improve the quality, transparency, and efficiency of maintenance and repair procedures and minimize machine downtime and reduce overall maintenance costs and impact.

Step 3: Embrace statistical process control.

This method involves detecting production issues by studying data anomalies to get rid of root causes before they ruin entire assembly lines. With connected frontline worker solutions that are integrated with enterprise quality management systems, organizations can improve statistical process control by optimizing data collection and inspection procedures through their frontline workforce. This essentially transforms frontline workers into quality sensors that further enhance and empower overall quality efforts.

Real-world application: Tracking the number of defective goods on each production line can help with identifying the root of any issue and taking corrective action. Smart, connected worker technology improves tracking ability, optimizes data collection, and identifies issues faster, reducing the risk of product recalls, and preserving consumer trust.

Digitizing Quality in Manufacturing with Augmentir

Companies are adopting innovative new technologies, processes, and methods to improve quality, productivity, and collaboration efforts across the industrial arena. Guaranteeing quality in manufacturing boils down to standardizing processes. Every procedure should contribute to product value and be carried out in a unified way. Implementing smart, connected solutions and coupling them with AI-powered analytics opens new paths for manufacturers to step forward and improve how they approach quality in the production process and beyond.

By digitizing analog paper practices, you enable better quality control and standardization of inspection procedures which, in turn, strengthens your overall manufacturing operations. Augmentir can help with the digitization and transformation process. We understand the need for effective quality control, and we have demonstrated success in helping manufacturers improve quality on the production floor.

Check out our quality use cases, and request a live demo today to learn for yourself why companies are choosing Augmentir to help standardize and digitize quality control procedures.

 

See Augmentir in Action
Get in Touch for a Personalized Demo

 

Book A Demo

How an Asset Hierarchy Can Help with Asset Maintenance

Learn about what an asset hierarchy is and how it can help with asset maintenance and equipment reliability.

An asset hierarchy outlines all of a business’s top equipment, machines, and components visually to help the business plan, execute and track maintenance activities. Asset hierarchies are usually in the shape of a pyramid, similar to an organizational chart. And since every operation is different, it’s likely you won’t have the same hierarchy as your competitor.

The benefits of an asset hierarchy include accurate maintenance planning, faster failure root cause analysis, and improved cost tracking. By implementing an asset hierarchy in conjunction with a frontline operations system, such as a connected worker solution, manufacturers can benefit by dramatically improved maintenance planning and execution. This article answers the following questions to help you learn more:

asset hierarchy improves maintenance

What is an asset hierarchy?

An asset hierarchy is an index of your most critical equipment, machines, and parts to better understand how these assets work together and monitor their maintenance needs. For example, building and maintaining your manufacturing business’s hierarchy can help you track and identify root causes of failure in your equipment.asset hierarchy and taxonomy - iso standard

This taxonomy is often represented as a pyramid, based on the ISO 14224 standard, which was developed for the collection and exchange of
reliability and maintenance data for equipment. Initially developed for the Petroleum, Petrochemical, and Natural Gas industry, this taxonomy for equipment and failure data can apply to any manufacturing environment, and has become the de-facto standard for every other industry.

Asset hierarchies are typically built and maintained within an organization’s EAM (Enterprise Asset Management) or CMMS (Computerized Maintenance Management System), which tracks asset maintenance and condition data, as well as maintenance schedules. Increasingly, EAMs, CMMS, and asset hierarchy information are being integrated with digitized frontline operations systems to improve maintenance planning and execution.

Pro Tip

It’s not enough to simply define your asset hierarchy with your EAM or CMMS. Innovative manufacturing companies are now extending this by integrating their asset hierarchies with connected worker solutions, which help digitize and optimize the actual work being done by frontline maintenance teams, improving maintenance execution.

A

Better organization of equipment can also help workers understand how the action of one affects the other to solve any potential problems. This is another benefit of integrating your asset hierarchy with a connected worker solution. In a nutshell, strong hierarchies are a solid foundation for proper maintenance management and reliability.

What is asset maintenance?

While maintenance is generally synonymous with repair, in effective manufacturing facilities, maintaining equipment can prevent the need for repairs. Asset maintenance is an umbrella term for everything that goes into keeping your assets in tip-top shape.

For example, asset maintenance in manufacturing machinery may mean frequent inspections to prevent breakdowns and repairs. Your space as a whole relies on this type of maintenance to ensure everything is running smoothly, from equipment to everyday production processes.

Lastly, this term makes daily manufacturing processes more productive to manage. That’s because effective asset management tells you where assets are located, how they are used, and when changes were made to them.

How does an asset hierarchy improve asset maintenance?

An asset hierarchy and asset maintenance work in conjunction with one another. This visual tool gives workers a better idea of what each asset is and the dependencies between them.

Knowing what each asset is can help you schedule preventative inspections and tasks. If any problems arise, you can more easily identify all the working parts, find the root cause and fix it.

 

Augmentir’s AI-powered asset management software helps you simplify the operations and maintenance of your facility by integrating your asset hierarchy and maintenance data within a frontline operations system. Through Augmentir, organizations can benefit from a complete view of asset management, all through a visual mobile interface. Each asset contains a complete view of:

  • Kanban board for all asset activities
  • Work and maintenance procedures
  • Skills required for operation and maintenance
  • Collaboration related to the asset
  • Associated documentation
  • CIL/Standard Work schedule
  • History of all activities on the asset

Asset management with Augmentir

Augmentir’s asset management capabilities include an out-of-the-box autonomous maintenance solution, which gives equipment operators more control over equipment cleaning, inspections, and lubrications (CIL) to improve CIL completion rate, resulting in minimized machine downtime.

Request a live demo today to learn why companies are choosing Augmentir to help standardize and digitize their maintenance activities.

 

See Augmentir in Action
Get in Touch for a Personalized Demo

 

Book A Demo

New LNS Research Report Highlights Augmentir as Leading Connected Frontline Workforce Solution

LNS Research reviewed dozens of Connected Frontline Worker (CFW) vendors, ranking Augmentir as the leading CFW solution innovator.

Efforts to enable the frontline industrial workforce through connected worker and other digital technologies have become increasingly common over the past several years, recently, LNS Research found that over half of industrial organizations globally have undertaken Connected Frontline Workforce (CFW) initiatives. CFW has become a strategic part of Industrial Transformation (IX) initiatives as manufacturers seek to solve critical labor shortages, skills gaps, and retention issues in frontline operations.

CFW-enabling technologies hold the promise of helping companies meet their frontline workforce challenges while optimizing operational performance across safety, quality, and productivity dimensions. However, industrial business and technology leaders must navigate the uncertain waters of the relatively immature and highly fragmented CFW Applications market to capture the opportunity fully.

LNS Research Connected Worker Solution Selection Matrix

From their extensive analysis, LNS Research has created the CFW Applications Solution Selection Matrix™ (SSM) – a comprehensive guide intended to help man­ufacturers better understand, evaluate, and even select from a shortlist of Connected Frontline Worker technology vendors.

LNS Research reviewed dozens of vendors within the CFW ecosystem and categorized them based on various key criteria, including product capabilities, market potential, and company presence.  Augmentir was named by LNS Research as a leading CFW solution innovator in their SSM.

Augmentir positioned as a leading front runner and innovator

According to LNS Research, Augmentir is well-positioned for future growth, with a trajectory that gives it the potential to be among a small set of likely market leaders in the Connected Frontline Worker (CFW) Applications space. This assessment is based partly on the strength of differentiated capabilities of its AI-enabled solution suite to enable proactive, data-driven performance improvement, personalization of work execution support and training, and the integration of individual and team skills and qualifications to guide workforce development and shift-specific work assignment.

Other key factors impacting Augmentir’s potential are the strength and proven experience of the leadership and management teams, strong momentum in the market, a record of successful product innovation, ecosystem partnerships, and likely continued access to adequate funding and resources to support the expansion of go-to-market initiatives. Augmentir’s track record indicates a strong likelihood of continued growth and the potential over time to be among a select group of market leaders in the CFW Applications space.

Read the full report here.

Augmentir’s results from the field

Manufacturers are using connected frontline worker solutions to empower their employees with real-time, actionable data; driving better decision-making and improving safety, training, and more.

Leading manufacturers that deployed Augmentir’s AI-driven, smart, connected worker solution have seen impressive results, such as:

  • 75% reduction in new hire training/onboarding time
  • 27% reduction in machine downtime using Autonomous Maintenance
  • 32% improvement in worker productivity

In addition to the above results, our customers have seen quality, safety, and productivity increases across all operations, as well as increases in employee retention and reductions in operating costs associated with employee churn.

 

If you are interested in learning why LNS Research ranked Augmentir as the leading connected worker solution in the market, reach out to us and request a live demo.

 

See Augmentir in Action
Get in Touch for a Personalized Demo

 

Book A Demo

How to Improve Quality Control and Quality Assurance in the Food Industry

Learn how to improve quality control and assurance in the food industry with digital solutions from Augmentir.

Following quality control (QC) and quality assurance procedures in the food industry is imperative to ensure product quality and consumer satisfaction. Today’s consumers demand safe, reliable goods that meet all quality inspection protocols. The last thing you want is for a product to get recalled because of potential health concerns.

According to Food Manufacturing, quality control is one of the most important aspects of the food and beverage industry. Manufacturers who perform routine inspections of products during each stage of the production process significantly increase their chances of delivering items that are free of health hazards and liabilities. But beyond avoiding these concerns, standardizing and digitizing quality procedures benefits the entire operation.

Ultimately, preventing and catching quality issues can boost product quality, reduce waste, raise profits, increase brand reputation, and avoid media or food safety disasters. Learn more about QC and assurance in the food industry and how to improve it as we discuss:

quality control food industry

Types of quality control measures to take

There are certain QC measures you can take to ensure that all goods meet quality standards, from regular machine inspections to worker training. They fall into two general categories: preventative and reactive.

Preventative (proactive) quality control: Minimizing the number of deficiencies begins with implementing preventative QC solutions. When workers can catch mistakes before they even happen, they prevent product defects. Preventative QC measures should be practiced on a routine basis and can range from inspecting machines and equipment to offering employee training opportunities. By providing workers with real-time information and guidance through mobile, connected worker solutions, manufacturers enable them to make better decisions about product quality, reducing the risk of errors and identifying potential quality issues before products are shipped to customers, reducing the risk of product recalls, and preserving consumer trust.

Reactive quality control: Catching every defect on the production floor is nearly impossible, even if the most fool-proof strategies are taken. That’s why creating a plan of action ahead of a crisis can help solve quality issues as they happen.

What to put in your plan will depend on the potential problems. For example, you can include specific instructions on what to do if machinery breaks down or stops unexpectedly. It’s vital to collect any data at this stage. Analyzing this data can help you improve preventative quality control in the future to make sure the same problems don’t happen again.

Pro Tip

By utilizing AI and modern, digital technologies, companies can connect, engage, and empower frontline workers to drive quality improvements, resolve quality issues faster, and share timely insights with teams across the value chain.

A

Keep in mind that practicing quality control in the food industry should be part of every manufacturing process, from product ideation and development to production and delivery. Problems can develop at any time, so it’s crucial to follow protocols at every stage of production to prevent even the slightest of mistakes.

All workers should also uphold QC and assurance protocols in their everyday tasks to ensure continuous product improvement.

Better organization of equipment can also help workers understand how the action of one affects the other to solve any potential problems. This is another benefit of integrating your asset hierarchy with a connected worker solution. In a nutshell, strong hierarchies are a solid foundation for proper maintenance management and reliability.

How to improve QC and assurance procedures in food production

Effective quality control and assurance procedures prevent defective food products from making their way into grocery stores and homes. That’s why manufacturers should document the quality of their goods at every stage of the operational process. Strategies like first time quality (FTQ), or first time right, plans coupled with smart, connected solutions help decrease product deficiencies and increase customer satisfaction.

Manufacturing firms in the food industry must follow specific requirements set by the Food and Drug Administration (FDA), Good Manufacturing Practices (GMP) system, and the Hazard Analysis and Critical Control Points (HACCP). The guidelines set by these regulatory bodies can give businesses a better idea of how their processes should look and what data they need to collect and report.

Data should be collected for real-time production processes. These vary by product but may range from product chilling and thermal processing to testing raw materials for metal toxins and other chemical deposits.

The following steps provide a roadmap for how to improve quality control in the food industry.

Step 1: Source the correct ingredients

A successful assembly line run begins with finding and using the correct ingredients. Some things to think about when deciding which ingredients to choose: where the raw material was sourced, when, and its condition.

Step 2: Include an approved supplier list

Make sure that each ingredient has an approved supplier list. A good rule of thumb is to include three vendors per ingredient and record the ingredient with each supplier’s name, address, and code number on the list. The more information you include, the better. Having an approved vendor list ensures that all parties are properly vetted by the manufacturing firm and meet its requirements for quality and distribution.

Step 3: Document product and recipe creation

Documenting how each food item is made and its recipe helps set the quality standards for finished goods. This documentation can also be useful when improving product development in the future. Your document should include the types of ingredients used, their codes, batch yield, percentage formula, and more.

Step 4: Catalog production procedures

It’s also critical to log all the details of a production process, including how materials should be delivered, the appropriate conditions for storing food, what order each ingredient should be added to the batch, what tools are needed, and who is in charge of each task.

Note that this step is different from documenting product and recipe development because it includes the actual instructions for carrying out each procedure. For example, a worker may be asked to preheat the oven to a certain temperature as part of ensuring the food is ready for customer distribution.

Step 4: Record real-time processes

Machine operators should record in real-time every detail of how goods are created during actual production. This can include factors like product size, weight, expiration date, equipment conditions, and more.

Step 5: Digitize assurance and inspection processes

AI and smart, connected worker systems help digitize and link inspections and other quality control procedures. This creates an additional layer of defense, protecting customers and preventing quality issues before they can impact production.

How Augmentir helps with quality control and assurance

Augmentir offers a smarter way to improve quality control in the food industry by effectively standardizing and optimizing quality assurance and inspection procedures for all frontline workers. With our smart, connected solutions coupled with AI-powered software, food manufacturers have improved quality control and assurance by:

  • Tracking and analyzing data to identify trends and opportunities for improvements
  • Reducing human error in inspections by standardizing and improving training procedures and processes
  • Transforming connected workers into human sensors who can proactively address quality and safety events that surface during manufacturing operations

standardize and digitize quality assurance procedures

 

Our AI-powered connected worker solutions, provide digital work instructions to help employees better perform inspection checks and reduce the number of production errors and rework.

These customized solutions also include:

  • Digital standard operating procedures (SOPs) for how to complete assembly line tasks. These step-by-step instructions can greatly improve workflow efficiency, increase regulatory compliance, and reduce mistakes on the shop floor.
  • Digital workflows that convert your paper-based processes to digital work instructions and personalize them to the needs of each worker.
  • Enhanced product traceability to decrease equipment setup time, reduce process inconsistencies, and better meet customer expectations. Our digital instructions help you to easily track materials from the supply chain, inventory, and across every production process.

If you are interested in learning why companies are choosing Augmentir to help improve their quality control and assurance processes, check out our quality use cases – or reach out to schedule a live demo.

 

See Augmentir in Action
Get in Touch for a Personalized Demo

 

Book A Demo

Why Manufacturing Data Collection is Important and How to Improve It

Learn how manufacturing data collection can boost your bottom line and how to improve your gathering data techniques.

As manufacturing operations continue to modernize and evolve it is clear that without big data they won’t be able to sustain themselves. More and more manufacturers are looking to the tremendous capabilities and insights that digitized information can provide.

Shop floor data collection enables businesses to better measure, standardize, and optimize their production processes. It’s more important than ever before to have information that provides real-time insights for measurable progress.

Accurate reporting is more sustainable if management deploys a work culture and production infrastructure that supports digitized manufacturing data collection with connected worker platforms and solutions.

We discuss more about collecting data and how to improve it in the following sections:

manufacturing data collection

Examples of data collection in manufacturing

Data collection has many uses in a variety of situations for a wide array of manufacturing roles, from operators and engineers to plant managers and even leadership.

For example:

  • Plant managers use production dashboards to better gauge where operators need support, such as when a piece of equipment isn’t working.
  • Operators use machine interfaces that show the status of machine processes, part counts, and other measurable data to ensure they are meeting production targets.
  • Quality managers use production line data to identify and proactively address quality issues.
  • Engineers use collected data to check for any bottlenecks and adjust processes if necessary.
Pro Tip

Frontline workers often witness safety, quality, or maintenance issues on the factory floor. They are effectively a “human sensor” on the manufacturing process and can readily identify issues that need to be addressed. Today, recording data and resolving those issues is most often a manual and paper-based process. As such, there is minimal data collection, latency in resolving the issue, and little-to-no feedback to the frontline worker on resolution.

Equipping workers with mobile and digital tools can help optimize shop floor data collection.

A

Which data to keep an eye on

Data generated on the shop floor can vary depending on the nature of work, the type of devices and technologies used, and the area of operation. Much of this data is of use to manufacturers and can be used to improve production processes.

Useful types of data for manufacturers that we recommend keeping an eye on are:

Inventory data: This type of data helps manufacturers keep track of product inventory. With it they can better gauge what items need to be restocked or which ones aren’t bringing any value to the customer as well as improve forecasting ability and more.

Quality and Inspection data: Ensuring product quality is a priority in manufacturing. Collecting data related to quality control, product inspection, and identifying defects or deviations from the desired standards is crucial to maintaining high-quality products and operations.

Machine data: Optimizing a production process can become difficult if you don’t know the status of your equipment. Manufacturing data collection can be digitized to analyze machine quality and performance, equipment runtime and downtimes, or other machine-related problems. Sensors monitor machine use and downtime, maintenance time, cycle time, and more. Studying this collected data helps identify where production can be improved to optimize efficiency.

Using AI, manufacturers can filter out the “white noise” data (or data that is of no use) to derive actionable insights more effectively than with traditional methods. Automating, standardizing, and digitizing manufacturing processes also improves manufacturing data collection procedures, making them streamlined, accurate, and reliable.

How to improve production data collection

Manufacturing data collection is transforming the way businesses handle their operational decisions. However, it can also pose setbacks to your production line if you gather inaccurate data.

Manufacturers must implement data collection systems that are easy to understand and navigate. You’re risking inconsistent data collection and reporting when you install a system with complicated functions and navigation tools. This can be avoided by focusing on people-centric, intuitive, and user-friendly systems that fit into the everyday flow of work for the frontline workforce.

quality manufacturing data collection

Implementing a unified system alone won’t improve data collection. Solutions that incorporate enhanced mobile capabilities and provide a truly connected enterprise are able to facilitate and optimize data collection efforts.

Examples of some useful smart, connected solutions to improve manufacturing data collection are:

  • Personalized, Digital Work Instructions: these intelligently deliver personalized digital work instructions matched to the needs of each worker in order to deftly guide them through and streamline day-to-day operations.
  • Connected Asset Management: these tools help simplify operations and maintenance of facilities, manage work and maintenance procedures, collaboration, and more.
  • Skills Management: these systems create visibility into workforce capability and optimize training programs, track individual and team progress, and initiate more targeted training and upskilling.

In addition to all the benefits listed above, these smart, connected worker tools are able to empower frontline workers with improved data-driven decision-making abilities that aid in safety, quality, and productivity efforts.

Benefits of digitizing shop floor data collection

Production data collection can make all the difference to a company’s success and give them a competitive edge. Smart, connected worker solutions enhance collection processes, allowing for real-time data collection, streamlined communication and collaboration between frontline workers.

Data-driven strategies can help with:

  • Creating better maintenance procedures based on real-time insights and equipment conditions
  • Optimizing worker productivity by minimizing production errors
  • Reducing downtime by providing real-time feedback
  • Developing higher quality products that increase customer satisfaction
  • Cutting supply chain costs due to better forecasting and waste reduction techniques

Implementing accurate, connected worker solutions can take your data collection efforts to the next level. That’s where Augmentir can help. We are the world’s only AI-driven, people-centric smart connected worker solution to standardize and optimize data collection using groundbreaking AI analytics technology.

See how our AI-focused connected worker solutions are driving results and improving data collection and data-driven decision-making across manufacturing operations – schedule a demo now.

 

See Augmentir in Action
Get in Touch for a Personalized Demo

 

Book A Demo

How to Improve Production Quality in Manufacturing

It’s vital that customers receive products that are free of defects. Learn 5 steps for improving production quality and how the right software can help.

Unexpected product quality issues can be a hassle to manage, especially when staff is stuck with processing time-consuming complaints, replacements, and refunds. Even worse, the impact on your bottom line can be substantial.

Manufacturers risk a significant cut to their profit margins when quality standards are not followed during the production process. To improve quality on the shop floor, plant managers need to pinpoint the root cause of quality issues.

Explore this article to learn how to start boosting your industrial processes today:

improve production quality in manufacturing

 

What is Production Quality

Production quality, or manufacturing quality, measures how well a manufacturing process develops products to fit design specifications. Manufacturers must devise a plan for how they want specific items to appear and function before creating them. This can include things like colors, durability, range of motion, measurements, and more. How well a product is made will depend on meeting these conditions.

After the design is planned, a number of factors can affect production quality, including:

  • Equipment/machines
  • Materials
  • Batch size
  • Human mistakes
  • Environmental issues
Pro Tip

Frontline workers often witness quality issues on the factory floor. They are effectively a “human sensor” in the manufacturing process and can readily identify issues that need to be addressed. Today, recording data and resolving those quality issues is most often a manual and paper-based process. As such, there is minimal data collection, latency in resolving the issue, and little-to-no feedback to the frontline worker on resolution.

Equipping workers with mobile and digital tools can help optimize production quality.

A

5 steps to improve production quality

Although there may not be one single method for improving manufacturing quality, there are steps you can take to maximize success.

Here are five steps that should be part of your strategy.

Step 1: Assess your current workflow.

Start by reviewing your existing manufacturing processes. We encourage management to ask the following questions as part of their review:

  • What quality benchmarks do you hope to achieve for each product?
  • How much money have you lost from material, energy waste, and wasted time due to quality problems?
  • What is your margin for improvement?
  • What quality standards are implemented in the creation of products?
  • Is your equipment inter-connected with different databases, or just a single database?

We recommend connecting your factory devices to one central database with a cloud-based, connected worker solution that operations management can use to create, assign, manage, and monitor the work being done. This kind of software can help streamline operational processes and track results in real-time.

Step 2: Remove unneeded processes.

Once you’ve accessed your current workflow and set up a connected worker solution to collect frontline worker data, we recommend coupling it with AI-powered analytics that can derive actionable insights. Then you can use these actionable, data-led insights to see which processes are adding value and which ones are not.

quality manufacturing data collection

Step 3: Boost worker training.

It’s important to maintain regular employee training and skills development programs to ensure workers are staying on top of industry best practices, equipment upkeep, and product knowledge. AI-powered connected worker solutions make learning more accessible, engaging, and effective.

Step 4: Create quality goals.

Developing quality goals is a great way to measure product benchmarks, production time, material usage, labor cost, working hours, and more. By digitizing and standardizing quality processes, you’ll be able to see which manufacturing processes are adding to your bottom line and which can be eliminated to bring value to the customer.

Step 5: Cut production waste.

Cutting waste from your production run can improve your business’s supply chain management. Connected worker solutions can identify which processes aren’t needed to reduce waste. It also gives real-time visibility into your supply chain to help you manage supply problems, optimize manufacturing processes, and adjust production schedules.

FAQs about improving production quality

How can the quality of the manufacturing industry be improved?

Measuring your current production processes to see which methods work can help improve product quality and increase the value of goods manufacturers make. You can strengthen the processes related to production by digitizing and automating them. Implementing a connected worker solution that offers real-time insights helps ensure that all goods meet quality standards and compliance criteria.

How do you ensure product quality in manufacturing?

There are a number of factors that can ensure product quality in manufacturing. We recommend following the five steps listed above to minimize defects as well as improve workflow and output.

What are 5 ways to improve production quality?

Assessing your current workflow, eliminating needless production processes, boosting work training, creating quality goals, and cutting production waste can all help improve production quality (see list above for a full description of each, as well as how implementing a connected worker solution can boost their overall impact).

Why is quality improvement important in manufacturing?

Enhancing production quality in manufacturing is a must as the industry moves towards fully connected enterprises, digital transformation, and automation. Businesses risk huge profit losses when quality standards are neglected in the creation of each product.

Digitize and Improve Production Quality with Augmentir

By digitizing and standardizing quality protocols, organizations can maintain compliance through an auditable and verifiable quality management system that gives workers access to the correct procedures as they need them with expert guidance. This ensures that tasks are performed in a standard manner to avoid errors on the production floor, reduce defects, and decrease resources lost to rework.

Refining your manufacturing methods can be difficult without the right technology. Augmentir’s AI-based connected worker solution makes streamlining and optimizing your production and quality procedures easier than ever before. Get in touch for a live demo today and learn why manufacturers are choosing Augmentir to help standardize and digitize quality processes!

 

See Augmentir in Action
Get in Touch for a Personalized Demo

 

Book A Demo

How to Reduce Changeover Time in Manufacturing

Learn how to reduce changeover time in manufacturing and the benefits of doing so to maximize production processes.

Providing quality products consistently and on time is at the forefront of customer satisfaction. In today’s competitive market, manufacturers must execute production runs quickly and efficiently to meet customer demand. But equipment and workers can’t operate 24/7. Machines must be properly maintained, workstations require cleaning and employees need rest. This is where optimizing changeover time comes in.

Changeover time is the period that it takes for workers to adjust machines or for assembly lines to start the next product run. A changeover usually includes swapping parts, sanitizing equipment, and preparing it for the next cycle. A good rule of thumb is to keep the changeover period down to less than 10 minutes. You can keep track of your organization’s changeover time by capturing how long it takes to produce each product.

Keeping an eye on your changeover time can help you maximize production and improve processes. Learn more about how you can reduce changeover time in manufacturing by exploring the following topics:

Three steps for reducing changeover time

Minimizing changeover time is a key component of lean manufacturing, a production method aimed at minimizing waste while increasing worker productivity. Implementation of this process can help manufacturers maximize uptime and cut down on waste caused by downtime.

Although there are various steps you can take to reduce it, here are some essential steps to help you get started:

Step 1: Assess your present changeover method.

It’s crucial to look at your existing changeover protocol before taking action to modify it. Try to identify which processes need optimization in order to cut down on the time between inventory runs.

Step 2: Implement single-minute exchange of dies (SMED).

Single-minute exchange of dies is a tool used in lean manufacturing to reduce changeover time to single digits. This means that a successful assembly run should be less than 10 minutes.

It’s helpful if workers have some idea of how long each task (such as switching parts, cleaning, etc.) takes during the production process. This awareness can be cultivated the more they familiarize themselves with procedures and day-to-day routines.

Step 3: Create standard changeover procedures.

Creating standard operating procedures (SOPs) and standardizing work can help with the changeover process. If there aren’t centralized procedures, changeover times will vary based on the employee, how long it takes them to clean up, set up and begin a new production run.

It’s important for procedures to contain explicit directions on how to perform successful changeovers. This can include highlighting which equipment needs to be calibrated and other machinery-related tasks.

Pro Tip

Digitizing changeover procedures can offer several benefits that enhance the overall efficiency, safety, and effectiveness of the changeover process. Digital procedures can be accessed by frontline workers through a mobile device or wearable technology, and help improve accessibility, accountability, standardization, as well as provide visual aids to less-experienced workers performing the task.

A

In a nutshell, having clear instructions makes it easier for workers to know what to expect when it’s time for a changeover.

Benefits of reducing changeover time

Reducing changeover time can yield a number of benefits, especially for companies producing a large number of products on a day-to-day basis.

Some of the advantages include:

  • Makes it easier to transition between production processes
  • Creates a more productive work environment
  • Helps to reduce equipment downtime
  • Gets products to customers faster

How digitization can help

Implementing connected worker solutions that digitize and optimize changeover processes can help reduce the time each changeover takes by providing explicit digital instructions customized to any given task, machine, or worker.

benefits of digital work instructions

Digital work instructions are electronic versions of work instructions, quality manuals, or SOPs that provide necessary visual aids and real-time contextual information to help guide workers through complex tasks. These digital work instructions intelligently deliver guidance and streamline changeover processes with images, videos, augmented reality experiences, and live support from colleagues or subject matter experts.

Augmentir is the world’s first AI-powered connected worker platform that helps industrial frontline workers reduce changeover time in manufacturing using smart technology. Learn how world class manufacturers are using Augmentir to drive improvements across their industrial operations – contact us for a demo today!

 

 

See Augmentir in Action
Get in Touch for a Personalized Demo
Book A Demo